Abstract: Objective This study aimed to characterize the long-term spatiotemporal dynamics of aquatic vegetation and its hydroclimatic responses in the Napahai seasonally plateau wetland, providing support for wetland conservation, water-soil resource regulation, and habitat management.Methods Based on Landsat and Sentinel-2 multisource remote sensing imagery from 1985 to 2024, a hierarchical aquatic habitat classification framework integrating spectral indices, adaptive thresholding, and random forest algorithms was developed. The framework was used to identify major habitat types, including emergent vegetation, submerged/floating-leaved vegetation, open water, and high-floating algae index (FAI) anomaly areas. Annual variations, habitat transition matrices, and Spearman correlation analyses were further applied to investigate long-term vegetation dynamics and their relationships with hydroclimatic factors. Results The proposed multisource remote sensing approach achieved an overall classification accuracy of 88.62% and a Kappa coefficient of 0.8115, demonstrating its effectiveness in identifying major aquatic habitat types in Napahai wetland. From 1985 to 2024, emergent vegetation, submerged/floating-leaved vegetation, and total aquatic vegetation exhibited pronounced interannual fluctuations and stage-dependent variations, without significant persistent increasing or decreasing trends. Spatially, aquatic vegetation was mainly distributed in shallow littoral zones and water–land transition areas, with long-term changes characterized primarily by dynamic conversions among aquatic vegetation, open water, and terrestrial vegetation. Aquatic vegetation areas showed significant correlations with annual precipitation, summer precipitation, and wet-season precipitation, suggesting that precipitation-driven hydrological processes may represent important environmental controls. High-FAI anomaly areas exhibited substantial spatiotemporal variability and were likely influenced by multiple factors, including phytoplankton accumulation, turbid water, and shallow-water substrate reflectance.Conclusion The multisource remote sensing-based hierarchical classification framework effectively reconstructed the long-term dynamics of aquatic vegetation in seasonal plateau wetlands. Aquatic vegetation changes in Napahai were primarily characterized by hydrologically regulated habitat shifts and boundary fluctuations rather than persistent expansion or degradation. These findings provide long-term data support for aquatic vegetation monitoring, karst watershed water–soil resource management, and ecological conservation of plateau wetlands.